您当前的位置:
首页 >
文章列表页 >
Study on fault area discrimination of ultra-high voltage three-terminal hybrid DC transmission line based on CNN-BiLSTM-Attention
更新时间:2026-10-18
    • Study on fault area discrimination of ultra-high voltage three-terminal hybrid DC transmission line based on CNN-BiLSTM-Attention

    • Electric Machines and Control   Vol. 29, Issue 7, Pages: 132-141(2025)
    • DOI:10.15938/j.emc.2025.07.013    

      CLC: TM721
    • Received:03 January 2024,

      Published:2025-07

    移动端阅览

  • CHEN Shilong, SONG Guoxiong, DENG Jian, et al. Study on fault area discrimination of ultra-high voltage three-terminal hybrid DC transmission line based on CNN-BiLSTM-Attention[J]. Electric Machines and Control, 2025, 29(7): 132-141. DOI: 10.15938/j.emc.2025.07.013.

  •  
  •  

0

Views

96

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Rolling bearing fault diagnosis with multi-scale multi-task attention convolutional neural network
Fault diagnosis of multi-sensor fusion permanent magnet synchronous motor based on residual convolutional neural network
Influence of functionalized fullerene doping on space charge and dielectric properties of 500 kV DC XLPE cable materials
Combined simulation model for partial discharge considering air-gap discharge, electromagnetic propagation and antenna response
Design of topology and dimensions for high-speed cage solid rotor induction motor

Related Author

WANG Zhaowei
LIU Chuanshuai
ZHAO Wenxiang
SONG Xiangjin
QIU Jianqi
SHEN Jiachen
SHI Cenwei
SHI Tingna

Related Institution

School of Electrical and Information Engineering, Jiangsu University
School of Electrical Engineering, Zhejiang University
Zhejiang University Advanced Electrical Equipment Innovation Center
School of Electrical and Information Engineering, Tianjin University
0